Mystery Shopping Analysis

Purchase Intent Based Analysis

If you don’t know where you are going, any road can take you there. Research without a clear direction in terms of identifying ways to improve the customer experience, may at times be interesting, but ultimately will fail to achieve a return on investment (ROI). Kinēsis builds call to action elements into our contact center research design, call to action elements which will provide a clear road map to maximize return on investment in the customer experience.

Kinēsis approach to building call to action into our research design is what we call Key Driver Analysis. To understand Key Driver Analysis, ask yourself what is the objective of the customer experience in terms to driving the thoughts, feeling and action of your customer? How do you want them to think, feel and act as a result of the customer experience? This is the objective of the customer experience. Key Driver Analysis provides clear direction in terms of identifying the attributes of the customer experience with the most potential for ROI in terms of driving this customer experience objective.

For most clients the desired outcomes are purchase intent or loyalty. For example, let’s assume the overall business objective of the customer experience is to increase customer loyalty as a result of the call. Key Driver Analysis determines the relationship of the various agent behaviors measured in the mystery shop to determine which behaviors are key drivers of loyalty. This provides a basis from which to make judgments on the relative importance of each behavior in terms of driving customer loyalty.

In the program design section, we described three main pillars of mystery shop questionnaire design: what, how and why. Research design should always anticipate the analysis. Here is how these design elements work in Key Driver Analysis:

Again, assuming the objective of the customer experience is to increase customer loyalty, shoppers are asked how the experience influenced their loyalty intent – the intent to maintain a relationship with the brand. By cross-tabulating and comparing shops with increased loyalty intent to shops with decreased loyalty intent it is possible to identify the specific attributes of the customer experience with the strongest relationship to customer loyalty. These are the attributes with the strongest potential for return on investment in terms of driving customer loyalty.

This loyalty intent rating is married to an open-ended question asking why the shopper rated their loyalty intent as they did. The responses are then grouped or classified by theme, yielding the frequency of themes contained in the shopper comments. Comparing themes in shops with high loyalty intent to those with low loyalty intent produces a highly qualitative picture of what specifically what drives customer loyalty.

Finally, managers need to know what agent behaviors drive loyalty. They need to know what behaviors have the largest potential for ROI in terms of driving customer loyalty. Gap analysis is such a tool. This quadrant-based analysis uses two dimensions:

First, the importance of each behavior. Importance defined by the strength of its relationship to loyalty.

Second, The performance of each behavior. Performance defined as the frequency with which it is observed in the mystery shops.

Graphing each behavior in this quadrant chart, like the one below, gives managers a means of identifying agent behaviors with the highest potential for return on investment in terms of driving customer loyalty.

This analysis helps contact center managers focus training, coaching, incentives, and other motivational tools directly on the agent behaviors which will produce the largest return on investment (behaviors with high importance and low performance).